Planktonic foraminifera eDNA signature deposited on the seafloor remains preserved after burial in marine sediments
Bibliographic record
Abstract
Environmental DNA (eDNA) metabarcoding of marine sediments has revealed large amounts of sequences assigned to planktonic taxa. How this planktonic eDNA is delivered on the seafloor and preserved in the sediment is not well understood. We address these questions by comparing metabarcoding and microfossil foraminifera assemblages in sediment cores taken off Newfoundland across a strong ecological gradient. We detected planktonic foraminifera eDNA down to 30 cm and observed that the planktonic/benthic amplicon ratio changed with depth. The relative proportion of planktonic foraminiferal amplicons remained low from the surface down to 10 cm, likely due to the presence of DNA from living benthic foraminifera. Below 10 cm, the relative proportion of planktonic foraminifera amplicons rocketed, likely reflecting the higher proportion of planktonic eDNA in the DNA burial flux. In addition, the microfossil and metabarcoding assemblages showed a congruent pattern indicating that planktonic foraminifera eDNA is deposited without substantial lateral advection and preserves regional biogeographical patterns, indicating deposition by a similar mechanism as the foraminiferal shells. Our study shows that the planktonic eDNA preserved in marine sediments has the potential to record climatic and biotic changes in the pelagic community with the same spatial and temporal resolution as microfossils.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".